Author: Tchelidze, L.
Paper Title Page
TUPC01 Overview of the European Spallation Source Warm Linac Beam Instrumentation 346
 
  • B. Cheymol, C. Böhme, I. Dolenc Kittelmann, H. Hassanzadegan, A. Jansson, T.J. Shea, L. Tchelidze
    ESS, Lund, Sweden
 
  The normal conducting front end of the European Spallation source will accelerate the beam coming for the ion source up to 90 MeV. The ESS front end will consist in an ion source, a low energy beam transport line, a radio frequency quadrupole, a medium energy beam transport line and a drift tube linac. The warm linac will be equipped with beam diagnostics to measure the beam position, the transverse and longitudinal profile as well as beam current and beam losses. This will provide efficient operation of ESS, and ensure keeping the losses at a low level. This paper gives an overview of the beam diagnostics design and their main features.  
 
WEPC45 Beam Loss Monitoring at the European Spallation Source 795
 
  • L. Tchelidze, H. Hassanzadegan, A. Jansson, M. Jarosz
    ESS, Lund, Sweden
 
  At the European Spallation Source proton linear accelerator will generate 5 MW protons to be delivered to a target. This high power accelerator will require significant amount of beam instrumentation, among which the beam loss monitoring system is one of the most important for operation. An LHC type ionization chamber will be used with ~54 uC/Gy sensitivity. At most 1.5 mGy/sec radiation levels are expected close to the beam pipe during normal operation, resulting in up to 80 nA current signal in detectors. Loss monitor electronics is designed to be able to measure currents as little as 1% of the expected current up to as much as 1% of the total beam loss, thus ~800 pA – few mA. In order to study beam loss pattern along the accelerator a coherent model of the whole machine is created for the purposes of Monte Carlo particle transport simulations. Data obtained using the model will be stored in a database together with the initial beam loss conditions. The contents of the database will then be processed using custom neural network algorithms to optimize number and position of the loss monitors and to provide reference on the beam loss localization during operation of the machine.  
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